Hybrid Movie Search System

Developed a hybrid multimodal movie search system that retrieves films using images (screenshots, frames), text descriptions, or combined queries. Built a large-scale pipeline with extensive data cleaning and deduplication, resulting in ~8,000 high-quality movies and 40,000+ vector embeddings. Used CLIP for joint image-text representations and FAISS for fast similarity search. Supports image-only, text-only, and weighted image+text retrieval with high accuracy.

#machinelearining #searchengine #computervision #python